refinement-finetuned-mnli-1

This model is a fine-tuned version of mfreihaut/refinement-finetuned-mnli-1 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 6.9744

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	50	3.6639
No log	2.0	100	3.1760
No log	3.0	150	3.5147
No log	4.0	200	7.2978
No log	5.0	250	6.9823
No log	6.0	300	6.1548
No log	7.0	350	1.8893
No log	8.0	400	3.4601
No log	9.0	450	5.1852
0.9791	10.0	500	5.1913
0.9791	11.0	550	2.7786
0.9791	12.0	600	6.8241
0.9791	13.0	650	5.2724
0.9791	14.0	700	4.7973
0.9791	15.0	750	6.1139
0.9791	16.0	800	6.5590
0.9791	17.0	850	5.6065
0.9791	18.0	900	6.4056
0.9791	19.0	950	5.7737
0.3292	20.0	1000	5.6033
0.3292	21.0	1050	6.8969
0.3292	22.0	1100	6.3766
0.3292	23.0	1150	6.1115
0.3292	24.0	1200	6.3750
0.3292	25.0	1250	6.3604
0.3292	26.0	1300	6.4051
0.3292	27.0	1350	6.7069
0.3292	28.0	1400	6.3017
0.3292	29.0	1450	6.9539
0.2482	30.0	1500	6.9133
0.2482	31.0	1550	6.5188
0.2482	32.0	1600	6.7478
0.2482	33.0	1650	6.5621
0.2482	34.0	1700	6.9490
0.2482	35.0	1750	6.6875
0.2482	36.0	1800	6.7723
0.2482	37.0	1850	6.5755
0.2482	38.0	1900	6.8727
0.2482	39.0	1950	6.8581
0.2245	40.0	2000	6.9993
0.2245	41.0	2050	7.1120
0.2245	42.0	2100	7.2491
0.2245	43.0	2150	7.0870
0.2245	44.0	2200	7.3960
0.2245	45.0	2250	7.0658
0.2245	46.0	2300	7.0175
0.2245	47.0	2350	7.0082
0.2245	48.0	2400	6.9570
0.2245	49.0	2450	6.9720
0.2124	50.0	2500	6.9744

Framework versions

• Transformers 4.22.2
• Pytorch 1.10.0
• Datasets 2.5.1
• Tokenizers 0.12.1